Epilepsy, a neurological disorder characterized by the occurrence of seizures (specifically episodic impairment or loss of consciousness, abnormal motor phenomena, psychic or sensory disturbances, or the perturbation of the autonomic nervous system), is debilitating to a great number of people. It is believed that as many as two to four million Americans may suffer from various forms of epilepsy. Research has found that its prevalence may be even greater worldwide, particularly in less economically developed nations, suggesting that the worldwide figure for epilepsy sufferers may be in excess of one hundred million.
Because epilepsy is characterized by seizures, its sufferers are frequently limited in the kinds of activities they may participate in. Epilepsy can prevent people from driving, working, or otherwise participating in much of what society has to offer. Some epilepsy sufferers have serious seizures so frequently that they are effectively incapacitated.
Furthermore, epilepsy is often progressive and can be associated with degenerative disorders and conditions. Over time, epileptic seizures often become more frequent and more serious, and in particularly severe cases, are likely to lead to deterioration of other brain functions (including cognitive function) as well as physical impairments.
The current state of the art in treating neurological disorders, particularly epilepsy, typically involves drug therapy and surgery. The first approach is usually drug therapy.
A number of drugs are approved and available for treating epilepsy, such as sodium valproate, phenobarbital/primidone, ethosuximide, gabapentin, phenytoin, and carbamazepine, as well as a number of others. Unfortunately, those drugs typically have serious side effects, especially toxicity, and it is extremely important in most cases to maintain a precise therapeutic serum level to avoid breakthrough seizures (if the dosage is too low) or toxic effects (if the dosage is too high). The need for patient discipline is high, especially when a patient's drug regimen causes unpleasant side effects the patient may wish to avoid.
Moreover, while many patients respond well to drug therapy alone, a significant number (at least 20-30%) do not. For those patients, surgery is presently the best-established and most viable alternative course of treatment.
Currently practiced surgical approaches include radical surgical resection such as hemispherectomy, corticectomy, lobectomy and partial lobectomy, and less-radical lesionectomy, transection, and stereotactic ablation. Besides being less than fully successful, these surgical approaches generally have a high risk of complications, and can often result in damage to eloquent (i.e., functionally important) brain regions and the consequent long-term impairment of various cognitive and other neurological functions. Furthermore, for a variety of reasons, such surgical treatments are contraindicated in a substantial number of patients. And unfortunately, even after radical brain surgery, many epilepsy patients are still not seizure-free.
Electrical stimulation is an emerging therapy for treating epilepsy. However, currently approved and available electrical stimulation devices apply continuous electrical stimulation to neural tissue surrounding or near implanted electrodes, and do not perform any detection—they are not responsive to relevant neurological conditions.
The NeuroCybernetic Prosthesis (NCP) from Cyberonics, for example, applies continuous electrical stimulation to the patient's vagus nerve. This approach has been found to reduce seizures by about 50% in about 50% of patients. Unfortunately, a much greater reduction in the incidence of seizures is needed to provide clinical benefit. The Activa device from Medtronic is a pectorally implanted continuous deep brain stimulator intended primarily to treat Parkinson's disease; it has also been tested for epilepsy. In operation, it supplies a continuous electrical pulse stream to a selected deep brain structure where an electrode has been implanted.
Continuous stimulation of deep brain structures for the treatment of epilepsy has not met with consistent success. To be effective in terminating seizures, it is believed that one effective site where stimulation should be performed is near the focus of the epileptogenic region of the brain. The focus is often in the neocortex, where continuous stimulation may cause significant neurological deficit with clinical symptoms including loss of speech, sensory disorders, or involuntary motion. Accordingly, research has been directed toward automatic responsive epilepsy treatment based on a detection of imminent seizure.
A typical epilepsy patient experiences episodic attacks or seizures, which are characterized by periods of abnormal neurological activity. “Epileptiform” activity refers to specific neurological activity associated with epilepsy as well as with an epileptic seizure and its precursors.
Most prior work on the detection and responsive treatment of seizures via electrical stimulation has focused on analysis of electroencephalogram (EEG) and electrocorticogram (ECoG) waveforms. In common usage, the term “EEG” is often used to refer to signals representing aggregate neuronal activity potentials detectable via electrodes applied to a patient's scalp, though the term can also refer to signals obtained from deep in the patient's brain via depth electrodes and the like. Specifically, “ECoGs” refer to signals obtained from internal electrodes near the surface of the brain (generally on or under the dura mater); an ECoG is a particular type of EEG. Unless the context clearly and expressly indicates otherwise, the term “EEG” shall be used generically herein to refer to both EEG and ECoG signals, regardless of where in the patient's brain the electrodes are located.
It is generally preferable to be able to detect and treat a seizure at or near its beginning, or even before it begins. The beginning of a seizure is referred to herein as an “onset.” However, it is important to note that there are two general varieties of seizure onsets. A “clinical onset” represents the beginning of a seizure as manifested through observable clinical symptoms, such as involuntary muscle movements or neurophysiological effects such as lack of responsiveness. An “electrographic onset” refers to the beginning of detectable electrographic activity indicative of a seizure. An electrographic onset will frequently occur before the corresponding clinical onset, enabling intervention before the patient suffers symptoms, but that is not always the case. In addition, there are changes in the EEG that occur seconds or even minutes before the electrographic onset that can be identified and used to facilitate intervention before electrographic or clinical onsets occur. This capability would be considered seizure prediction, in contrast to the detection of a seizure or its onset.
Much of the work on seizure detection has focused on the analysis of EEG signals. See, e.g., J. Gotman, Automatic seizure detection: improvements and evaluation, Electroencephalogr. Clin. Neurophysiol. 1990; 76(4):317-24. In a typical time-domain detection system, EEG signals are received by one or more electrodes and then processed by a control module, which then is capable of performing an action (intervention, warning, recording, etc.) when an abnormal event is detected.
In the Gotman system, EEG waveforms are filtered and decomposed into features representing characteristics of interest in the waveforms. One such feature is characterized by the regular occurrence (i.e., density) of half-waves exceeding a threshold amplitude occurring in a specified frequency band between approximately 3 Hz and 20 Hz, especially in comparison to background (non-ictal) activity. When such half-waves are detected, it is believed that seizure activity is occurring. For related approaches, see also H. Qu and J. Gotman, A seizure warning system for long term epilepsy monitoring, Neurology 1995; 45:2250-4; and H. Qu and J. Gotman, A Patient-Specific Algorithm for the Detection of Seizure Onset in Long-Term EEG Monitoring: Possible Use as a Warning Device, IEEE Trans. Biomed. Eng. 1997; 44(2):115-22. See also U.S. Pat. No. 6,016,449 to Fischell et al. and U.S. application Ser. No. 09/896,092, filed on Jun. 28, 2001.
The known approaches to epileptic seizure detection do provide useful information, and in some cases may provide sufficient information for accurate detection and prediction of most imminent epileptic seizures. It is generally difficult, however, to achieve a high rate of success without extensively tuning or calibrating the detection algorithms. Moreover, even when a detection algorithm is believed to be well tuned, it may be subject to detection errors.
Two types of detection errors are generally possible. A false positive, as the term is used herein, refers to a detection of a seizure or onset when no clinical or electrographic seizure is actually occurring or about to occur. Similarly, a false negative herein refers to the failure to detect a seizure or onset when a clinical seizure actually is occurring or shortly will occur.
In most cases, with all known implementations of the known approaches to detecting abnormal seizure activity solely by monitoring and analyzing EEG activity, when a seizure detection algorithm is tuned to catch all seizures, there will be a significant number of false positives.
It has been suggested that it is possible to treat and terminate seizures by applying electrical stimulation to the brain. See, e.g., U.S. Pat. No. 6,016,449 to Fischell et al., H. R. Wagner, et al., Suppression of cortical epileptiform activity by generalized and localized ECoG desynchronization, Electroencephalogr. Clin. Neurophysiol. 1975; 39(5):499-506; and R. P. Lesser et al., Brief bursts of pulse stimulation terminate afterdischarges caused by cortical stimulation, Neurology 1999; 53(December):2073-81. And as stated above, it is believed to be beneficial to perform this stimulation only when a seizure (or other undesired neurological event) is occurring or about to occur, as inappropriate stimulation may result in the initiation of seizures. While it is currently believed that there are minimal or no side effects to over-treatment via electrical stimulation (e.g., providing stimulation sufficient to terminate a seizure in response to a false positive), the possibility of accidentally initiating a seizure, causing motor or sensory effects, or increasing the patient's susceptibility to seizures must be considered.
Furthermore, it should be noted that a false negative (that is, a seizure that occurs without any warning or treatment from the device) will often cause the patient significant discomfort and detriment. Clearly, false negatives are to be avoided.
Accordingly, to facilitate tuning or calibrating a device capable of detecting and treating epileptic seizures, there is a need to be able to set detection parameters for a variety of detection algorithms based on data received by an implantable neurostimulator. A system and method capable of performing such an action would set and refine parameters to achieve a clinically acceptable detection rate (number of actual seizures caught in comparison to number of actual seizures missed, or false negatives), a clinically acceptable false positive rate (number of seizures incorrectly identified), and clinically acceptable detection delays.
Fischell et al., in U.S. Pat. No. 6,128,538 (referenced above), describes an implantable neurostimulator for responsive treatment of neurological disorders. The Fischell invention further describes the neurostimulator having a seizure detection subsystem and a data recording subsystem capable of recording EEG signals and transferring the stored EEG signals to external equipment. In U.S. patent application Ser. No. 09/517,797, filed on Mar. 2, 2000 and entitled “Neurological Event Detection Using Processed Display Channel Based Algorithms and Devices Incorporating These Procedures,” which is hereby incorporated by reference as though set forth in full herein, Fischell and Harwood describe a system for selecting and combining EEG channels with one or more seizure detection algorithms to detect seizures.
In U.S. patent application Ser. No. 09/556,415, filed on Apr. 21, 2000 and entitled “System for the Creation of Patient Specific Templates for Epileptiform Activity Detection”, D. Fischell and J. Harwood also describe an iterative technique for allowing simultaneous display of annotated seizure records and an automated system for processing the records to produce a seizure detector template—namely a set of patient-specific detection or prediction parameters. However, the technique disclosed is not adapted for use with multiple short EEG records uploaded from an implantable device with limited storage capacity. Also Fischell and Harwood do not describe a means for choosing which template is preferred from a plurality of templates, and do not address template development or optimization with regard to any neurological event other than seizure onsets.
Neither U.S. patent application Ser. No. 09/556,415 nor U.S. Pat. No. 6,128,538 (both of which are referenced above) specifically addresses a system for optimizing seizure detector parameter settings through processing EEG data recorded by an implantable neurostimulator.